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The admission index in the dental school admissions process
Author(s) -
Staat RH,
Yancey JM
Publication year - 1982
Publication title -
journal of dental education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.53
H-Index - 68
eISSN - 1930-7837
pISSN - 0022-0337
DOI - 10.1002/j.0022-0337.1982.46.8.tb01576.x
Subject(s) - entrance exam , aptitude , test (biology) , pearson product moment correlation coefficient , medical education , psychology , index (typography) , medicine , mathematics education , predictive validity , statistics , mathematics , clinical psychology , computer science , developmental psychology , paleontology , world wide web , biology
Preprofessional students' grade point averages (GPAs) and aptitude test scores have been moderately successful in predicting student performance in dental school. The authors attempted to improve the predictability of the school's admission process by combining several preprofessional academic averages and selected nongraded personal attributes into a single Admission Index (AI) score. A Pearson r of 0.67 was found for the relationship between the AI and first‐year dental school GPA for University of Louisville dental students accepted into the class of 1984. The correlation coefficient generated from the AI and first‐year dental school GPA was markedly superior to those generated by any single predictor. The authors propose that the AI is of value not only for its use in the admission process, but also in the development of an interceptive student monitoring program for the less‐qualified student.